Wearables have become increasingly integrated into clinical practice, with continuous glucose monitors transforming diabetes management and wrist watches equipped with photoplethysmography allowing for arrhythmia detection.4,5 Dermatology offers a similarly promising opportunity for wearable integration, as many cutaneous conditions fluctuate between visits and rely on patient reported symptoms, which may be subject to recall bias. Objective quantification of pruritus, hydration, biomarkers, and sleep disturbance could complement subjective symptom reporting, enhancing disease monitoring.2 Devices such as the advanced acoustomechanic (ADAM) can detect scratching to objectively assess pruritus as well as sleep quality, aiding in the diagnosis of diseases such as AD and monitoring treatment responses.6,7 Skin hydration sensors have also shown promise in monitoring local environment for the management of AD, psoriasis, urticaria, xerosis cutis, or rosacea.8
In addition to skin localized sensors, physiologic wearables may provide insight into chronic inflammatory disorders. Heart rate variability (HRV) has been consistently associated with inflammation which provides a rationale for exploring HRV as a digital biomarker in dermatologic conditions.9 Cameron et al further link inflammation, sleep disturbances, and neurocognitive effects in AD, highlighting the relevance of wearable derived sleep and autonomic metrics in understanding disease severity.10 However, no dermatology-specific studies yet demonstrate flare prediction using physiologic wearables, underscoring an important gap in literature.
Despite their potential, little is known about dermatologists’ familiarity with and attitudes towards these devices. While clinician perspectives on the usage of wearables in monitoring inflammatory diseases such as COPD have been examined, dermatologists’ perspectives on these technologies remain underexplored.11 To address this gap, we conducted a 13-question survey at a national dermatology conference to assess awareness, usage, feasibility, and perceived utility of wearable devices in dermatologic practice. To our knowledge, this is the first survey to directly assess dermatologists’ perspectives on wearable adoption.
Familiarity with wearable devices was generally low, with 28.8% rating themselves 0 (least familiar) and 23.1% rating 1, while only 3.8% rated 3 and 13.5% rated 4 (highly familiar). Similarly, 34.6% felt unconfident educating patients about them. In addition, 43.1% had no plans to incorporate patient education on wearables within the next six months. Lack of training (43.3%) and cost to patients (45.0%) were cited as key barriers to the integration of wearables.
Despite limited plans for patient education on wearables, 87.6% rated the importance of physicians having knowledge about wearables as 2 or higher on a 0–4 scale. However, 75.4% of dermatologists reported that they do not integrate this data into electronic health records (EHR), suggesting another cause for limited clinical uptake. Fitness trackers were the most recommended devices (51.7%). Peer-reviewed literature was the most trusted source for interpreting wearable data (38.6%).
How old are you? (n=60)
≤29
16.7
10
30–39
50.0
30
40–49
15.0
9
50–59
8.3
5
60–69
5.0
3
≥70
5.0
3
What gender do you identify as? (n=59)
Man
45.8
27
Woman
54.2
32
Other
0
0
Where do you practice? (n=49)
Northwest
8.2
4
Northeast
24.5
12
Southwest
6.1
3
Southeast
26.5
13
South
16.3
8
Midwest
18.4
9
Years practicing (n=59)
Resident/Fellow
42.4
25
0–10 years
30.5
18
11–20 years
11.9
7
21–30 years
6.8
4
≥31 years
8.5
5
Familiarity with wearables (rated: 0-4; 0 least, 4 most) (n=52)
0
28.8
15
1
23.1
12
2
30.8
16
3
3.8
2
4
13.5
7
Comfort educating patients (rated: 0–4; 0 least, 4 most) (n=52)
0
34.6
18
1
11.5
6
2
30.8
16
3
15.4
8
4
7.7
4
Do you educate patients? (n=58)
No, no plans in 6 months
43.1
25
No, plan to start in 6 months
32.8
19
No, plan to start in 30 days
5.2
3
Yes, less than 6 months
15.5
9
Yes, more than 6 months
3.4
2
Importance of wearable knowledge (rated 0–4; 0 least, 4 most) (n=48)
0
8.3
4
1
4.2
2
2
41.7
20
3
27.1
13
4
18.8
9
Recommended wearables (n=60)
Continuous glucose monitors
31.7
19
Fitness trackers
51.7
31
Skin temperature monitors
6.7
4
Skin hydration sensors
6.7
4
ADAM devices
8.3
5
Other
11.7
7
Barriers to use (n=60)
Cost to patients
45.0
27
Lack of training/familiarity
43.3
26
Patient adherence
23.3
14
Integration issues
21.7
13
Data accuracy
11.7
7
Lack of evidence
15.0
9
No barriers
15.0
9
Other
3.3
2
Main reason for using wearables (n=57)
Improve outcomes
17.5
10
Real-time data
1.8
1
Enhance engagement/self-management
26.3
15
Reduce in-person visits
1.8
1
Do not use
49.1
28
Other
3.5
2
Guidelines used (n=57)
Peer-reviewed literature
38.6
22
Manufacturer guidelines
3.5
2
Internal protocols
7.0
4
Physician discretion
7.0
4
Do not use data
40.4
23
Other
3.5
2
EHR integration (n=57)
Not incorporated
75.4
43
Mentioned in notes
10.5
6
Input as discrete elements
7.0
4
Linked to third-party
5.3
3
Other
1.8
1
Epidermal sensors allow for direct, non-invasive interface with the skin to measure local biochemical parameters.1,3 For example, wearable skin hydration sensors performed reliably across multiple body locations.8 This device showed validated accuracy by producing average skin hydration values in healthy volunteers consistent with established literature and demonstrated the ability to distinguish lesional from non-lesional skin in inflammatory conditions such as atopic dermatitis and psoriasis, supporting its potential role as an adjunct to existing diagnostic and management tools.8
Pruritus is a hallmark of several dermatologic diseases, yet traditionally assessed via patient report. Wireless sensors act through acoustomechanic signals to quantify pruritus and have shown strong agreement with video-confirmed scratching events demonstrating their validity.6 Similarly, hand mounted wearable sensors have shown reliable discrimination between scratching and non-scratching movements in adults with AD.7
HRV and restorative sleep cycles are sensitive indicators of autonomic nervous system balance and recovery capacity. In chronic inflammatory diseases, reduced HRV and disrupted sleep, particularly the proportion of deep and REM sleep, often correlate with heightened systemic inflammation and impaired tissue repair.9,10 By continuously tracking HRV, and potentially sleep disturbances, patients and clinicians can detect early signs of inflammatory flares or insufficient recovery.9,13 Evidence from other inflammatory diseases supports this approach. Hirten et al demonstrated that wearable-derived physiologic data could identify and predict inflammatory bowel disease flares, suggesting that similar methodologies may eventually be applicable to dermatology.13 However, dermatology-specific evidence remains limited, and current data do not yet support the use of physiologic wearables alone for flare prediction in skin disease. Nevertheless, these measures may prove useful as adjunctive endpoints for assessing treatment response, medication effects, or overall disease burden in future studies, pending further validation.
This survey highlights a growing awareness of wearable technologies in dermatology, but also underscores a gap between recognition and practical use. Although most providers acknowledged the importance of wearable devices, nearly half reported no current usage or plans to educate patients, pointing to systemic barriers such as cost and lack of training. Notably, among providers who did report using wearables, the primary motivation was to enhance patient engagement and self-management, reflecting their potential to empower patients and promote active participation in care. The discrepancy between awareness and adoption mirrors a larger challenge in digital health, patients are increasingly using wearable monitors, yet clinicians remain uncertain about how to integrate these data into care. EHR integration remains limited, with three out of four physicians reporting no routine incorporation of wearable data. Cost also remains a concern. Without institutional support or insurance reimbursement, wearables risk becoming tools that disproportionately benefit patients of higher socioeconomic status, widening the existing health disparities between classes.14
Education gaps further limit wearable device adoption, with over half of respondents reporting minimal familiarity with wearable devices. Addressing these gaps through continuing medical education or research presentations could help mitigate this limitation in familiarity and promote clinical usage. Generating more data on wearables through interventional studies, justifying medical necessity scenarios, and promoting insurance coverage for wearable devices may also improve adoption. Real-world implementation research could clarify workflow feasibility. Addressing cost concerns and improving provider familiarity may also reduce hesitancy and expand access, especially in underserved populations.3,15
Limitations include small sample size, geographic concentration, and potential biases. The concentration of respondents in the Southeast and Northeast regions of the United States may limit generalizability. Future research should explore objective usage data and broader sampling to validate these findings and inform policy and clinical integration.
IRB, institutional review board
None declared.
None
Reviewed and approved by Medical University of South Carolina IRB; Pro00141717
Not applicable
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